Evidence map›Paper›PMID 39577867›Full record

Trial reportBMJ quality & safety2025

Comparing safety, performance and user perceptions of a patient-specific indication-based prescribing tool with current practice: a mixed methods randomised user testing study.

Calandra Feather, Jonathan Clarke, Nicholas Appelbaum, Ara Darzi, Bryony Dean Franklin

Registry-linked trialAbstract readRandomized Controlled TrialComparative Study
In one paragraph

Trial report in BMJ quality & safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05493072 (Safety, Performance, and User Perceptions of RxConnect When Used to Provide Patient-specific, Indication Based Prescribing Support), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05493072 nacompletednot on this map

Safety, Performance, and User Perceptions of RxConnect When Used to Provide Patient-specific, Indication Based Prescribing Support

TypeinterventionalSponsorImperial College LondonRan2022 to 2023Enrolled24ConditionsBehaviorArmsRxConnect
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Calandra FeatherDepartment of Surgery and Cancer, Imperial College London, London, UK c.feather@imperial.ac.uk.ORCID http://orcid.org/0000-0003-1322-6589
Jonathan ClarkeDepartment of Mathematics, Imperial College London, London, UK.ORCID http://orcid.org/0000-0003-1495-7746
Nicholas AppelbaumDepartment of Surgery and Cancer, Imperial College London, London, UK.
Ara DarziDepartment of Surgery and Cancer, Imperial College London, London, UK.
Bryony Dean FranklinDirector, Centre for Medication Safety and Service Quality, Imperial College Healthcare NHS Trust, London, UK.ORCID http://orcid.org/0000-0002-2892-1245

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedication errors are the leading cause of preventable harm in healthcare. Despite proliferation of medication-related clinical decision support systems (CDSS), current systems have limitations. We therefore developed an indication-based prescribing tool. This performs dose calculations using an underlying formulary and provides patient-specific dosing recommendations. Objectives were to compare the incidence and types of erroneous medication orders, time to prescribe (TTP) and perceived workload using the NASA Task Load Index (TLX), in simulated prescribing tasks with and without this intervention. We also sought to identify the workflow steps most vulnerable to error and to gain participant feedback.

methodsA simulated, randomised, cross-over exploratory study was conducted at a London NHS Trust. Participants completed five simulated prescribing tasks with, and five without, the intervention. Data collection methods comprised direct observation of prescribing tasks, self-reported task load and semistructured interviews. A concurrent triangulation design combined quantitative and qualitative data.

results24 participants completed a total of 240 medication orders. The intervention was associated with fewer prescribing errors (6.6% of 120 orders) compared with standard practice (28.3% of 120 orders; odds ratio 0.18, p<0.01), a shorter TTP and lower overall NASA-TLX scores (p<0.01). Control arm workflow vulnerabilities included failures in identifying correct doses, applying maximum dose limits and calculating patient-specific dosages. Intervention arm errors primarily stemmed from misidentifying patient-specific information from the medication scenario. Thematic analysis of participant interviews identified six themes: navigating trust and familiarity, addressing challenges and suggestions for improvement, integration of local guidelines and existing CDSS, intervention endorsement, 'search by indication' and targeting specific patient and staff groups.

conclusionThe intervention represents a promising advancement in medication safety, with implications for enhancing patient safety and efficiency. Further real-world evaluation and development of the system to meet the needs of more diverse patient groups, users and healthcare settings is now required. TRIAL REGISTRATION NUMBER: NCT05493072.

Indexed as

Decision Support Systems, ClinicalDrug PrescriptionsMedication ErrorsPatient SafetyAdultCross-Over StudiesFemaleHumansLondonMaleWorkloadDecision support, clinicalMedication safetyPatient safetyRandomised controlled trialSimulation

Identifiers

PMID39577867
PMCPMC12573381

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.